Automatic summarizer text in Swift

Models to perform neural summarization (extractive and abstractive) using machine learning transformers and a tool to convert abstractive summarization datasets to the extractive task.

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation net…

Machine learning models to automatically summarise scientific papers

A tool to automatically summarize documents abstractively using the BART or PreSumm Machine Learning Model.

Python implementation of AutoPlait (SIGMOD'14) without smoothing algorithm. NOTE: This repository is for my personal use.

微博自动摘要系统 Chinese Microblog Automatic Summary System

The Internet plays an increasingly important part in our daily lives as a source of written content for news and leisure. Yet it is tedious and difficult to sort through this staggering flow of information and stay updated with changes in our world, even using automated tools. Reading magazines and newspapers is too time-consuming, and there is …

Tool to extracts the text from a web article urls and get frequency words, entities recognition, automatic summary and more

Bridging Video Content and Comments: Synchronized Video Description with Temporal Summarization of Crowdsourced Time-Sync Comments

A script to process the ArXiv-PubMed dataset.

Automatic summarisation of Medicines's Description

MOTS (MOdular Tool for Summarization) is a summarization system, written in Java. It is as modular as possible, and is intended to provide an architecture to implement and test new summarization methods, as well as to ease comparison with already implemented methods, in an unified framework.

Automatic Extractive Text Summarization using NLTK library implemented using Python, by tokenizing the sentences, finding the weighted frequency of occurrence, and calculating sentence scores for generation of concise summaries from extensive textual content.

LinTO's NLP service: Extractive Summarization

Content Summary Generator

using feature maximisation for summarizing scientifc documents

Data collection and resulting timelines for the paper Summarize Dates First: A Paradigm Shift in Timeline Summarization published at SIGIR 2021

Code for paper 'Summary Refinement through Denoising'

Evaluation and agreement scripts for the DISCOSUMO project. Each evaluation script takes both manual annotations as automatic summarization output. The formatting of these files is highly project-specific. However, the evaluation functions for precision, recall, ROUGE, Jaccard, Cohen's kappa and Fleiss' kappa may be applicable to other domains too.